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dc.contributor.authorSnášel, Václav
dc.contributor.authorPlatoš, Jan
dc.contributor.authorKrömer, Pavel
dc.contributor.authorAbraham, Ajith
dc.contributor.authorOuddane, Nabil
dc.contributor.authorHúsek, Dušan
dc.date.accessioned2011-01-07T08:19:13Z
dc.date.available2011-01-07T08:19:13Z
dc.date.issued2010
dc.identifier.citationNeural network world : international journal on non-standard computing and artificial intelligence. 2010, vol. 20, issue 5, p. 591-608.en
dc.identifier.issn1210-0552
dc.identifier.urihttp://hdl.handle.net/10084/83522
dc.description.abstractSince their appearance in 1993, first approaching the Shannon limit, turbo codes have given a new direction in the channel encoding field, especially since they have been adopted for multiple norms of telecommunications such as deeper communication. A robust interleaver can significantly contribute to the overall performance a turbo code system. Search for a good interleaver is a complex combinatorial optimization problem. In this paper, we present genetic algorithms and differential evolution, two bio-inspired approaches that have proven the ability to solve non-trivial combinatorial optimization tasks, as promising optimization methods to find a well-performing interleaver for large frame sizes.en
dc.language.isoenen
dc.publisherAkademie věd České republiky, Ústav informatikyen
dc.publisherČeské vysoké učení technické v Praze. Fakulta dopravní
dc.relation.ispartofseriesNeural network world : international journal on non-standard computing and artificial intelligenceen
dc.titleInterleaver optimization using population based metaheuristicsen
dc.typearticleen
dc.identifier.locationNení ve fondu ÚKen
dc.identifier.wos000284915500002


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